Plasma sFlt-1/PlGF ratio of 11.5 multiples of median predicts preeclampsia with severe features within two weeks of testing.

BACKGROUND: Angiogenic imbalances, characterized by an excess of antiangiogenic factors (soluble fms-like tyrosine kinase 1 [sFlt-1]) and reduced angiogenic factors (VEGF and placental growth factor [PlGF]), contribute to the mechanisms of disease in preeclampsia. The ratio of sFlt-1 to PlGF has been used as a biomarker for preeclampsia, but cut-off values may vary with gestational age and assay platform. OBJECTIVES: To compare multiples of the median (MoM) of maternal plasma sFlt-1/PlGF ratio, sFlt-1, PlGF, and conventional clinical and laboratory values to predict preeclampsia with severe features. STUDY DESIGN: We conducted a cohort study across 18 U.S. centers involving hospitalized hypertensive individuals between 23-35 weeks' gestation. Receiver operating characteristic curve (ROC) analyses of maternal plasma biomarkers, highest systolic or diastolic blood pressures, and laboratory values at enrollment were performed for the prediction of preeclampsia with severe features. Their areas under the curve (AUC) were compared, and quasi-Poisson regression models were fitted to estimate relative risks. The primary outcome was preeclampsia with severe features within two weeks of enrollment. Secondary outcomes were a composite of severe adverse maternal outcomes (elevated liver enzymes, low platelets count, placental abruption, eclampsia, disseminated intravascular coagulation, and pulmonary edema) and a composite of severe adverse perinatal outcomes (birthweight <3rd percentile, very preterm birth [<32 weeks] and fetal/neonatal death). RESULTS: Out of 543 individuals included in the study, preeclampsia with severe features within two weeks was observed in 33.1% (n=180) of them. A ROC-derived cut-off of 11.5 MoM for sFlt-1/PlGF plasma ratio provided sensitivity (90.6%), specificity (76.9%), positive predictive value (66.0%), negative predictive value (94.3%), positive likelihood ratio (3.91), negative likelihood ratio (0.12), and accuracy (81.4%) for preeclampsia with severe features within two weeks. This cut-off was used to compare test positive cases (≥ cut-off) and test negative cases (< cut-off). Preeclampsia with severe features (66.0% vs. 5.7%; <0.001), and composites of severe adverse maternal (8.11% vs. 2.7%; p=0.006) or perinatal outcomes (41.3% vs. 10.14%; p=0.001) within two weeks were more frequent in test positive cases than test negative cases. sFlt-1/PlGF plasma ratio ≥11.5 MoM was independently associated with preeclampsia with severe features (adjusted incidence rate ratio [aIRR]: 9.08, 95% CI: 6.11 to 14.06; p<0.001) and a composite of severe adverse perinatal outcomes (aIRR: 9.42, 95% CI: 6.36 to 14.53; p<0.001), but not with a composite of severe adverse maternal outcomes (aIRR: 2.20, 95% CI: 0.95 to 5.54; p=0.08).The AUC of sFlt-1/PlGF plasma ratio in MoM (0.91; 95% CI: 0.89-0.94) for preeclampsia with severe features within two weeks was significantly higher (p<0.001 for all comparisons) than either plasma biomarker alone or any other parameter, with the exception of absolute sFlt-1/PlGF plasma ratio values. CONCLUSIONS: SFlt-1/PlGF plasma ratio ≥11.5 MoM among hospitalized, hypertensive patients between 23- and 35-week's gestation predicts progression to preeclampsia with severe features and severe adverse perinatal outcomes within two weeks.

Genetic polymorphisms associated with adverse pregnancy outcomes in nulliparas.

Adverse pregnancy outcomes (APOs) affect a large proportion of pregnancies and represent an important cause of morbidity and mortality worldwide. Yet the pathophysiology of APOs is poorly understood, limiting our ability to prevent and treat these conditions. To search for genetic markers of maternal risk for four APOs, we performed multi-ancestry genome-wide association studies (GWAS) for pregnancy loss, gestational length, gestational diabetes, and preeclampsia. We clustered participants by their genetic ancestry and focused our analyses on three sub-cohorts with the largest sample sizes: European, African, and Admixed American. Association tests were carried out separately for each sub-cohort and then meta-analyzed together. Two novel loci were significantly associated with an increased risk of pregnancy loss: a cluster of SNPs located downstream of the TRMU gene (top SNP: rs142795512), and the SNP rs62021480 near RGMA. In the GWAS of gestational length we identified two new variants, rs2550487 and rs58548906 near WFDC1 and AC005052.1, respectively. Lastly, three new loci were significantly associated with gestational diabetes (top SNPs: rs72956265, rs10890563, rs79596863), located on or near ZBTB20, GUCY1A2, and RPL7P20, respectively. Fourteen loci previously correlated with preterm birth, gestational diabetes, and preeclampsia were found to be associated with these outcomes as well.

Socioeconomic Disadvantage in Pregnancy and Postpartum Risk of Cardiovascular Disease.

BACKGROUND: Pregnancy is an educable and actionable life stage to address social determinants of health (SDOH) and lifelong cardiovascular disease (CVD) prevention. But the link between a risk score that combines multiple neighborhood-level social determinants in pregnancy and the risk of long-term CVD remains to be evaluated. OBJECTIVE: To examine whether neighborhood-level socioeconomic disadvantage measured by the Area Deprivation Index (ADI) in early pregnancy is associated with a higher 30-year predicted risk of CVD postpartum, as measured by the Framingham Risk Score. METHODS: An analysis of data from the prospective Nulliparous Pregnancy Outcomes Study-Monitoring Mothers-to-Be (nuMoM2b) Heart Health Study longitudinal cohort. Participant home addresses during early pregnancy were geocoded at the Census-block level. The exposure was neighborhood-level socioeconomic disadvantage using the 2015 ADI by tertile (least deprived [T1], reference; most deprived [T3]) measured in the first trimester. Outcomes were the predicted 30-year risks of atherosclerotic CVD (ASCVD, composite of fatal and non-fatal coronary heart disease and stroke) and total CVD (composite of ASCVD plus coronary insufficiency, angina pectoris, transient ischemic attack, intermittent claudication, and heart failure) using the Framingham Risk Score measured 2-to-7 years after delivery. These outcomes were assessed as continuous measures of absolute estimated risk in increments of 1%, and, secondarily, as categorical measures with high-risk defined as an estimated probability of CVD >10%. Multivariable linear regression and modified Poisson regression models adjusted for baseline age and individual-level social determinants, including health insurance, educational attainment, and household poverty. RESULTS: Among 4,309 nulliparous individuals at baseline, the median age was 27 years (IQR: 23-31) and the median ADI was 43 (IQR: 22-74). At 2-to-7 years postpartum (median: 3.1 years, IQR: 2.5, 3.7), the median 30-year risk of ASCVD was 2.3% (IQR: 1.5, 3.5) and of total CVD was 5.5% (IQR: 3.7, 7.9); 2.2% and 14.3% of individuals had predicted 30-year risk >10%, respectively. Individuals living in the highest ADI tertile had a higher predicted risk of 30-year ASCVD % (adj. ß: 0.41; 95% CI: 0.19, 0.63) compared with those in the lowest tertile; and those living in the top two ADI tertiles had higher absolute risks of 30-year total CVD % (T2: adj. ß: 0.37; 95% CI: 0.03, 0.72; T3: adj. ß: 0.74; 95% CI: 0.36, 1.13). Similarly, individuals living in neighborhoods in the highest ADI tertile were more likely to have a high 30-year predicted risk of ASCVD (aRR: 2.21; 95% CI: 1.21, 4.02) and total CVD ≥10% (aRR: 1.35; 95% CI: 1.08, 1.69). CONCLUSIONS: Neighborhood-level socioeconomic disadvantage in early pregnancy was associated with a higher estimated long-term risk of CVD postpartum. Incorporating aggregated SDOH into existing clinical workflows and future research in pregnancy could reduce disparities in maternal cardiovascular health across the lifespan, and requires further study.

A Multi-Site Study to Develop and Validate First Trimester, Circulating Microparticle Biomarkers for Tiered Risk Stratification of Spontaneous Preterm Birth in Nulliparas.

BACKGROUND: Despite much research, advances in early prediction of spontaneous preterm birth (sPTB) has been slow. The evolving field of circulating microparticle (CMP) biology may identify novel blood-based, and clinically useful, biomarkers. OBJECTIVE: To test the ability of a previously identified, 7-marker set of CMP-derived proteins from the first trimester of pregnancy, in the form of an in vitro diagnostic multivariate index assay (IVDMIA), to stratify pregnant patients according to their risk for sPTB. STUDY DESIGN: We employed a previously validated set of CMP protein biomarkers, utilizing mass spectrometry assays and a nested case-control design in a subset of participants from the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be (nuMoM2b). We evaluated these biomarkers in the form of an IVDMIA to predict risk for sPTB at different gestational ages. Plasma samples collected at 9- to 13-weeks' gestation were analyzed. The IVDMIA assigned subjects to one of three sPTB risk categories: low risk (LR), moderate risk (MR), or high risk (HR). Independent validation on a set-aside set confirmed the IVDMIA's performance in risk stratification. RESULTS: Samples from 400 participants from the nuMoM2b cohort were used for the study; of these, 160 delivered <37 weeks and 240 delivered at term. Through Monte Carlo simulation in which the validation results were adjusted based on actual weekly sPTB incidence rates in the nuMoM2b cohort, the IVDMIA stratifications demonstrated statistically significant differences among the risk groups in time-to-event (birth) analysis (p < 0.0001). The incidence-rate adjusted cumulative risks of sPTB at ≤ 32 weeks' gestation were 0.4%, 1.6%, and 7.5%, respectively for the LR, MR, and HR groups, respectively. Compared to the LR group, the corresponding risk ratios (RR) of the IVDMIA assigned MR and HR group were 4.25 (95% CI 2.2 to 7.9) and 19.92 (95% CI 10.4 to 37.4), respectively. CONCLUSION: A first trimester CMP protein biomarker panel can be used to stratify risk for sPTB at different gestational ages. Such a multi-tiered stratification tool could be used to assess risk early in pregnancy to enable timely clinical management and interventions, and, ultimately, to enable the development of tailored care pathways for sPTB prevention.

Stillbirth: We can do better.

Stillbirth is far too common, occurring in millions of pregnancies per year globally. The rate of stillbirth (defined as death of a fetus prior to birth at 20 weeks' gestation or more) in the United States is 5.73 per 1,000. This is approximately 1 in 175 pregnancies accounting for about 21,000 stillbirths per year. Although rates are much higher in low-income countries, the stillbirth rate in the U.S. is much higher than most high resource countries. Moreover, there are substantial disparities in stillbirth, with rates twice as high for non-Hispanic Black and Native Hawaiian or Other Pacific Islanders compared to non-Hispanic Whites. There is considerable opportunity for reduction in stillbirths, even in high resource countries such as the U.S. In this article, we review the epidemiology, risk factors, causes, evaluation, medical and emotional management, and prevention of stillbirth. We focus on novel data regarding genetic etiologies, placental assessment, risk stratification, and prevention.

Adverse Pregnancy Outcomes and Pharyngeal Flow Limitation during Sleep: Nulliparous Pregnancy Outcomes Study Monitoring Mothers-to-be (nuMoM2b).

RATIONALE: Pharyngeal flow limitation during pregnancy may be a risk factor for adverse pregnancy outcomes but was previously challenging to quantify. OBJECTIVE: To determine whether a novel objective measure of flow limitation identifies an increased risk of preeclampsia (primary outcome) and other adverse outcomes in a prospective cohort: Nulliparous Pregnancy Outcomes Study Monitoring Mothers-to-be. METHODS: Flow limitation severity scores (0%=fully obstructed, 100%=open airway)- quantified from breath-by-breath airflow shape-were obtained from home sleep tests during early (6-15 weeks) and mid (22-31 weeks) pregnancy. Multivariable logistic regression quantified associations between flow limitation (median overnight severity, both time-points averaged) and preeclampsia, adjusting for maternal age, body mass index (BMI), race, ethnicity, chronic hypertension, and flow limitation during wakefulness. Secondary outcomes were hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus (GDM), and infant birthweight. RESULTS: Of 1939 participants with flow limitation data at both time-points (age: 27.0±5.4 yr [mean±sd], BMI: 27.7±6.1 kg·m-2), 5.8% developed preeclampsia, 12.7% developed HDP, and 4.5% developed GDM. Greater flow limitation was associated with increased preeclampsia risk: adjusted Odds Ratio (OR) 2.49, 95% Confidence Interval [1.69, 3.69], per 2SD increase in severity. Findings persisted in women without sleep apnea (apnea-hypopnea index <5 events·hr-1). Flow limitation was associated with HDP (OR: 1.77 [1.33, 2.38]) and reduced infant birthweight (83.7 [31.8, 135.6] g), but not GDM. CONCLUSIONS: Greater flow limitation is associated with increased risk of preeclampsia, HDP, and lower infant birthweight. Flow limitation may provide an early target for mitigating the consequences of sleep disordered breathing during pregnancy.

Prediction of metabolic syndrome following a first pregnancy.

BACKGROUND: The prevalence of metabolic syndrome is rapidly increasing in the United States. We hypothesized that prediction models using data obtained during pregnancy can accurately predict the future development of metabolic syndrome. OBJECTIVE: This study aimed to develop machine learning models to predict the development of metabolic syndrome using factors ascertained in nulliparous pregnant individuals. STUDY DESIGN: This was a secondary analysis of a prospective cohort study (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be Heart Health Study [nuMoM2b-HHS]). Data were collected from October 2010 to October 2020, and analyzed from July 2023 to October 2023. Participants had in-person visits 2 to 7 years after their first delivery. The primary outcome was metabolic syndrome, defined by the National Cholesterol Education Program Adult Treatment Panel III criteria, which was measured within 2 to 7 years after delivery. A total of 127 variables that were obtained during pregnancy were evaluated. The data set was randomly split into a training set (70%) and a test set (30%). We developed a random forest model and a lasso regression model using variables obtained during pregnancy. We compared the area under the receiver operating characteristic curve for both models. Using the model with the better area under the receiver operating characteristic curve, we developed models that included fewer variables based on SHAP (SHapley Additive exPlanations) values and compared them with the original model. The final model chosen would have fewer variables and noninferior areas under the receiver operating characteristic curve. RESULTS: A total of 4225 individuals met the inclusion criteria; the mean (standard deviation) age was 27.0 (5.6) years. Of these, 754 (17.8%) developed metabolic syndrome. The area under the receiver operating characteristic curve of the random forest model was 0.878 (95% confidence interval, 0.846-0.909), which was higher than the 0.850 of the lasso model (95% confidence interval, 0.811-0.888; P<.001). Therefore, random forest models using fewer variables were developed. The random forest model with the top 3 variables (high-density lipoprotein, insulin, and high-sensitivity C-reactive protein) was chosen as the final model because it had the area under the receiver operating characteristic curve of 0.867 (95% confidence interval, 0.839-0.895), which was not inferior to the original model (P=.08). The area under the receiver operating characteristic curve of the final model in the test set was 0.847 (95% confidence interval, 0.821-0.873). An online application of the final model was developed (https://kawakita.shinyapps.io/metabolic/). CONCLUSION: We developed a model that can accurately predict the development of metabolic syndrome in 2 to 7 years after delivery.

Serum exosomal microRNA pathway activation in placenta accreta spectrum: pathophysiology and detection.

BACKGROUND: Placenta accreta spectrum disorders are a complex range of placental pathologies that are associated with significant maternal morbidity and mortality. A diagnosis of placenta accreta spectrum relies on ultrasonographic findings with modest positive predictive value. Exosomal microRNAs are small RNA molecules that reflect the cellular processes of the origin tissues. OBJECTIVE: We aimed to explore exosomal microRNA expression to understand placenta accreta spectrum pathology and clinical use for placenta accreta spectrum detection. STUDY DESIGN: This study was a biomarker analysis of prospectively collected samples at 2 academic institutions from 2011 to 2022. Plasma specimens were collected from patients with suspected placenta accreta spectrum, placenta previa, or repeat cesarean deliveries. Exosomes were quantified and characterized by nanoparticle tracking analysis and western blotting. MicroRNA were assessed by polymerase chain reaction array and targeted single quantification. MicroRNA pathway analysis was performed using the Ingenuity Pathway Analyses software. Placental biopsies were taken from all groups and analyzed by polymerase chain reaction and whole cell enzyme-linked immunosorbent assay. Receiver operating characteristic curve univariate analysis was performed for the use of microRNA in the prediction of placenta accreta spectrum. Clinically relevant outcomes were collected from abstracted medical records. RESULTS: Plasma specimens were analyzed from a total of 120 subjects (60 placenta accreta spectrum, 30 placenta previa, and 30 control). Isolated plasma exosomes had a mean size of 71.5 nm and were 10 times greater in placenta accreta spectrum specimens (20 vs 2 particles/frame). Protein expression of exosomes was positive for intracellular adhesion molecule 1, flotilin, annexin, and CD9. MicroRNA analysis showed increased detection of 3 microRNAs (mir-92, -103, and -192) in patients with placenta accreta spectrum. Pathway interaction assessment revealed differential regulation of p53 signaling in placenta accreta spectrum and of erythroblastic oncogene B2 or human epidermal growth factor 2 in control specimens. These findings were subsequently confirmed in placental protein analysis. Placental microRNA paralleled plasma exosomal microRNA expression. Biomarker assessment of placenta accreta spectrum signature microRNA had an area under the receiver operating characteristic curve of 0.81 (P<.001; 95% confidence interval, 0.73-0.89) with a sensitivity and specificity of 89.2% and 80%, respectively. CONCLUSION: In this large cohort, plasma exosomal microRNA assessment revealed differentially expressed pathways in placenta accreta spectrum, and these microRNAs are potential biomarkers for the detection of placenta accreta spectrum.

The Role of cfDNA Biomarkers and Patient Data in the Early Prediction of Preeclampsia: Artificial Intelligence Model.

OBJECTIVE: Accurate individualized assessment of preeclampsia risk enables the identification of patients most likely to benefit from initiation of low-dose aspirin at 12-16 weeks' gestation when there is evidence for its effectiveness, as well as guiding appropriate pregnancy care pathways and surveillance. The primary objective of this study was to evaluate the performance of artificial neural network models for the prediction of preterm preeclampsia (<37 weeks' gestation) using patient characteristics available at the first antenatal visit and data from prenatal cell-free DNA (cfDNA) screening. Secondary outcomes were prediction of early onset preeclampsia (<34 weeks' gestation) and term preeclampsia (≥37 weeks' gestation). METHODS: This secondary analysis of a prospective, multicenter, observational prenatal cfDNA screening study (SMART) included singleton pregnancies with known pregnancy outcomes. Thirteen patient characteristics that are routinely collected at the first prenatal visit and two characteristics of cfDNA, total cfDNA and fetal fraction (FF), were used to develop predictive models for early-onset (<34 weeks), preterm (<37 weeks), and term (≥37 weeks) preeclampsia. For the models, the 'reference' classifier was a shallow logistic regression (LR) model. We also explored several feedforward (non-linear) neural network (NN) architectures with one or more hidden layers and compared their performance with the LR model. We selected a simple NN model built with one hidden layer and made up of 15 units. RESULTS: Of 17,520 participants included in the final analysis, 72 (0.4%) developed early onset, 251 (1.4%) preterm, and 420 (2.4%) term preeclampsia. Median gestational age at cfDNA measurement was 12.6 weeks and 2,155 (12.3%) had their cfDNA measurement at 16 weeks' gestation or greater. Preeclampsia was associated with higher total cfDNA (median 362.3 versus 339.0 copies/ml cfDNA; p<0.001) and lower FF (median 7.5% versus 9.4%; p<0.001). The expected, cross-validated area under the curve (AUC) scores for early onset, preterm, and term preeclampsia were 0.782, 0.801, and 0.712, respectively for the LR model, and 0.797, 0.800, and 0.713, respectively for the NN model. At a screen-positive rate of 15%, sensitivity for preterm preeclampsia was 58.4% (95% CI 0.569, 0.599) for the LR model and 59.3% (95% CI 0.578, 0.608) for the NN model.The contribution of both total cfDNA and FF to the prediction of term and preterm preeclampsia was negligible. For early-onset preeclampsia, removal of the total cfDNA and FF features from the NN model was associated with a 6.9% decrease in sensitivity at a 15% screen positive rate, from 54.9% (95% CI 52.9-56.9) to 48.0% (95% CI 45.0-51.0). CONCLUSION: Routinely available patient characteristics and cfDNA markers can be used to predict preeclampsia with performance comparable to other patient characteristic models for the prediction of preterm preeclampsia. Both LR and NN models showed similar performance.

NuMoM2b Study Insights: Primary Exposures, Outcomes, and Directions for Future Research.

OBJECTIVE: To summarize the publications to date from a large obstetric cohort of nulliparous individuals. STUDY DESIGN: We summarized all of the publications from the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be (nuMoM2b). We descriptively summarized the most common outcomes and exposures reported in current publications. RESULTS: Fifty-six publications to date are discussed. The most common primary exposures reported are participant baseline characteristics such as body mass index (24%), sociodemographic characteristics (22%), and sleep factors (16%). These exposures were most commonly measured in the first trimester (77%). The most commonly reported primary outcomes were related to adverse pregnancy outcomes (APOs, 51.6%), with 25% using a composite of multiple APOs as the primary outcome. At least 8,000 participants were used in the analyses of over half of the publications. CONCLUSION: The nuMoM2b study has generated a diverse array of publications and conclusions on factors associated with APOs. The publicly available data set from the nuMoM2b study continues to hold potential for considerable advances, new insights, and future research opportunities to optimize pregnancy and pregnancy-related health. KEY POINTS: · The nuMoM2b pregnancy cohort has generated 56 publications thus far.. · The main findings of these publications are summarized and categorized in this work.. · The data and specimens from this cohort are available and can answer many clinical questions..

Allostatic load in early pregnancy and sleep-disordered breathing.

OBJECTIVES: To assess the association between allostatic load in early pregnancy and sleep-disordered breathing (SDB) during pregnancy. METHODS: High allostatic load in the first trimester was defined as ≥ 4 of 12 biomarkers (systolic blood pressure, diastolic blood pressure, body mass index, cholesterol, low-density lipoprotein, high-density lipoprotein, high sensitivity C-reactive protein, triglycerides, insulin, glucose, creatinine, and albumin) in the unfavorable quartile. SDB was objectively measured using the Embletta-Gold device and operationalized as "SDB ever" in early (6-15 weeks) or mid-pregnancy (22-31 weeks); SDB at each time point was analyzed as secondary outcomes. Multivariable logistic regression was used to test the association between high allostatic load and SDB, adjusted for confounders. Moderation and sensitivity analyses were conducted to assess the role of allostatic load in racial disparities of SDB and obesity affected the relationship between allostatic load and SDB. RESULTS: High allostatic load was present in 35.0% of the nuMoM2b cohort. The prevalence of SDB ever occurred among 8.3% during pregnancy. After adjustment, allostatic load remained significantly associated with SDB ever (aOR= 5.3; 3.6-7.9), in early-pregnancy (aOR= 7.0; 3.8-12.8), and in mid-pregnancy (aOR= 5.8; 3.7-9.1). The association between allostatic load and SDB was not significantly different for people with and without obesity. After excluding BMI from the allostatic load score, the association decreased in magnitude (aOR= 2.6; 1.8-3.9). CONCLUSION: The association between allostatic load and SDB was independent of confounders including BMI. The complex and likely bidirectional relationship between chronic stress and SDB deserves further study in reducing SDB.

Community-level social determinants of health and pregestational and gestational diabetes.

BACKGROUND: Individual adverse social determinants of health are associated with increased risk of diabetes in pregnancy, but the relative influence of neighborhood or community-level social determinants of health is unknown. OBJECTIVE: This study aimed to determine whether living in neighborhoods with greater socioeconomic disadvantage, food deserts, or less walkability was associated with having pregestational diabetes and developing gestational diabetes. STUDY DESIGN: We conducted a secondary analysis of the prospective Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be. Home addresses in the first trimester were geocoded at the census tract level. The exposures (modeled separately) were the following 3 neighborhood-level measures of adverse social determinants of health: (1) socioeconomic disadvantage, defined by the Area Deprivation Index and measured in tertiles from the lowest tertile (ie, least disadvantage [T1]) to the highest (ie, most disadvantage [T3]); (2) food desert, defined by the United States Department of Agriculture Food Access Research Atlas (yes/no by low income and low access criteria); and (3) less walkability, defined by the Environmental Protection Agency National Walkability Index (most walkable score [15.26-20.0] vs less walkable score [<15.26]). Multinomial logistic regression was used to model the odds of gestational diabetes or pregestational diabetes relative to no diabetes as the reference, adjusted for age at delivery, chronic hypertension, Medicaid insurance status, and low household income (<130% of the US poverty level). RESULTS: Among the 9155 assessed individuals, the mean Area Deprivation Index score was 39.0 (interquartile range, 19.0-71.0), 37.0% lived in a food desert, and 41.0% lived in a less walkable neighborhood. The frequency of pregestational and gestational diabetes diagnosis was 1.5% and 4.2%, respectively. Individuals living in a community in the highest tertile of socioeconomic disadvantage had increased odds of entering pregnancy with pregestational diabetes compared with those in the lowest tertile (T3 vs T1: 2.6% vs 0.8%; adjusted odds ratio, 2.52; 95% confidence interval, 1.41-4.48). Individuals living in a food desert (4.8% vs 4.0%; adjusted odds ratio, 1.37; 95% confidence interval, 1.06-1.77) and in a less walkable neighborhood (4.4% vs 3.8%; adjusted odds ratio, 1.33; 95% confidence interval, 1.04-1.71) had increased odds of gestational diabetes. There was no significant association between living in a food desert or a less walkable neighborhood and pregestational diabetes, or between socioeconomic disadvantage and gestational diabetes. CONCLUSION: Nulliparous individuals living in a neighborhood with higher socioeconomic disadvantage were at increased odds of entering pregnancy with pregestational diabetes, and those living in a food desert or a less walkable neighborhood were at increased odds of developing gestational diabetes, after controlling for known covariates.

Placental Lesions Associated With Stillbirth by Gestational Age, as Related to Cause of Death: Follow-Up Results From the Stillbirth Collaborative Research Network.

BACKGROUND: We previously identified placental lesions associated with stillbirths of varying gestational ages (GA) using advanced feature analysis. We further investigated the relationships between placental lesions and cause of death in stillbirths within these GA ranges. METHODS: Using data from the Stillbirth Collaborative Research Network, we derived a sample of stillbirths who underwent placental examination and Initial Causes of Fetal Death (INCODE) evaluation for determining cause of death. We then compared the rates of causes of death within and among GA ranges (extreme preterm stillbirth [PTSB] [<28 weeks], early PTSB [28-336/7 weeks], late PTSB [34-366/7 weeks], term stillbirth [≥37 weeks]) according to the presence of these lesions. RESULTS: We evaluated 352 stillbirths. In extreme PTSB, obstetric complications and infections were associated with acute funisitis. In early PTSB, uteroplacental insufficiency was associated with parenchymal infarcts. In term stillbirth (vs early PTSB), increased syncytial knots were associated with umbilical cord causes and infection. CONCLUSIONS: Placental lesions of high importance in distinguishing stillbirths at different GAs are associated with specific causes of death. This information is important in relating the presence of placental lesions and fetal death and in helping to understand etiologies of stillbirths at different GAs.

Copy number variants and fetal structural abnormalities in stillborn fetuses: A secondary analysis of the Stillbirth Collaborative Research Network study.

OBJECTIVE: To examine the association of placental and fetal DNA copy number variants (CNVs) with fetal structural malformations (FSMs) in stillborn fetuses. DESIGN: A secondary analysis of stillbirth cases in the Stillbirth Collaborative Research Network (SCRN) study. SETTING: Multicenter, 59 hospitals in five geographic regions in the USA. POPULATION: 388 stillbirth cases of the SCRN study (2006-2008). METHODS: Fetal structural malformations were grouped by anatomic system and specific malformation type (e.g. central nervous system, thoracic, cardiac, gastrointestinal, skeletal, umbilical cord and craniofacial defects). Single-nucleotide polymorphism array detected CNVs of at least 500 kb. CNVs were classified into two groups: normal, defined as no CNVs >500 kb or benign CNVs, and abnormal, defined as pathogenic or variants of unknown clinical significance. MAIN OUTCOME MEASURES: The proportions of abnormal CNVs and normal CNVs were compared between stillbirth cases with and without FSMs using the Wald Chi-square test. RESULTS: The proportion of stillbirth cases with any FSMs was higher among those with abnormal CNVs than among those with normal CNVs (47.5 versus 19.1%; P-value <0.001). The most common organ system-specific FSMs associated with abnormal CNVs were cardiac defects, followed by hydrops, craniofacial defects and skeletal defects. A pathogenic deletion of 1q21.1 involving 46 genes (e.g. CHD1L) and a duplication of 21q22.13 involving four genes (SIM2, CLDN14, CHAF1B, HLCS) were associated with a skeletal and cardiac defect, respectively. CONCLUSION: Specific CNVs involving several genes were associated with FSMs in stillborn fetuses. The findings warrant further investigation and may inform counselling and care surrounding pregnancies affected by FSMs at risk for stillbirth.